In this way you can offer your visitors structure when visiting the web shop. Some of our customers have a web shop with thousands of products and parts. In this case, it can be a lot of work to classify products into the various categories. With machine learning, you can have the computer automatically label and classify products into the appropriate categories and filters based on the product photo or other product data you have. For example, you can use the Commerce tools API for this or tinker with Tensor flow, Google Vision AI and Google Text Recognition API. 9. Crop Images An example of another useful application of machine learning is image cropping.
Some images contain a background or watermark or were not taken in a professional photo studio, which means that the photo is not nicely cropped. Machine learning can fix these imperfections for you, you can see an example of this at Remove BG . This way you ensure that your images are automatically suitable for your web shop and can be used job function email list directly in Google Shopping. Crop image 10. Product Recommendations Recommending relevant products based on the visitor's surfing and buying behavior is well known within the e-commerce world. With machine learning, this technique has become increasingly sophisticated. In many cases, the computer knows better which products you would like to buy more than if you set related products yourself as a web shop owner.
You can use Amazon Personalize for this, for example, but there are also ready-made modules that can offer this functionality for almost every e-commerce platform. Amazon Personalize 11. Fraud Detection A bit of a boring but no less important application of artificial intelligence is fraud detection. The computer is simply better at detecting unusual patterns or signs of fraud. Fraudsters often find new ways to circumvent existing systems because they are not self-learning. With machine learning, the system automatically adapts and can therefore also detect these tricks.